| E2Efold-3D: end-to-end deep learning method for accurate de novo RNA 3D structure prediction T Shen, Z Hu, Z Peng, J Chen, P Xiong, L Hong, L Zheng, Y Wang, I King, ... arXiv preprint arXiv:2207.01586, 2022 | 32 | 2022 |
| Interpretable RNA foundation model from unannotated data for highly accurate RNA structure and function predictions J Chen, Z Hu, S Sun, Q Tan, Y Wang, Q Yu, L Zong, L Hong, J Xiao, ... arXiv preprint arXiv:2204.00300, 2022 | 32 | 2022 |
| Deep autoencoder for interpretable tissue-adaptive deconvolution and cell-type-specific gene analysis Y Chen, Y Wang, Y Chen, Y Cheng, Y Wei, Y Li, J Wang, Y Wei, TF Chan, ... Nature Communications 13 (1), 6735, 2022 | 27 | 2022 |
| conST: an interpretable multi-modal contrastive learning framework for spatial transcriptomics Y Zong, T Yu, X Wang, Y Wang, Z Hu, Y Li BioRxiv, 2022.01. 14.476408, 2022 | 22 | 2022 |
| Con-AAE: contrastive cycle adversarial autoencoders for single-cell multi-omics alignment and integration X Wang, Z Hu, T Yu, Y Wang, R Wang, Y Wei, J Shu, J Ma, Y Li Bioinformatics 39 (4), btad162, 2023 | 10 | 2023 |
| CLMB: deep contrastive learning for robust metagenomic binning P Zhang, Z Jiang, Y Wang, Y Li International Conference on Research in Computational Molecular Biology, 326-348, 2022 | 8 | 2022 |
| A nonautonomous-differential-inclusion neurodynamic approach for nonsmooth distributed optimization on multi-agent systems X Wen, Y Wang, S Qin Neural Computing and Applications 33 (20), 13909-13920, 2021 | 6 | 2021 |
| AcrNET: predicting anti-CRISPR with deep learning Y Li, Y Wei, S Xu, Q Tan, L Zong, J Wang, Y Wang, J Chen, L Hong, Y Li Bioinformatics 39 (5), btad259, 2023 | 5 | 2023 |
| Progress and Opportunities of Foundation Models in Bioinformatics Q Li, Z Hu, Y Wang, L Li, Y Fan, I King, L Song, Y Li arXiv preprint arXiv:2402.04286, 2024 | 1 | 2024 |
| scNovel: a scalable deep learning-based network for novel rare cell discovery in single-cell transcriptomics C Zheng, Y Wang, Y Cheng, X Wang, H Wei, I King, Y Li Briefings in Bioinformatics 25 (3), bbae112, 2024 | | 2024 |
| scMinerva: an Unsupervised Graph Learning Framework with Label-efficient Fine-tuning for Single-cell Multi-omics Integrated Analysis T Yu, Y Zong, Y Wang, X Wang, Y Li bioRxiv, 2022.05. 28.493838, 2022 | | 2022 |
Irwin KingThe Chinese University of Hong KongVerified email at cse.cuhk.edu.hk
